multihop energy efficient reliable and fault tolerant routing

International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 2, February 2013)

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Multihop Energy Efficient Reliable and Fault Tolerant

Routing Protocol for Wireless

Sensor Networks K. Vinoth Kumar

1, S.Karthikeyan

2

1Assistant Professor, M.A.R College of Engg&Tech, Viralimalai, Tamil Nadu. 2PG Scholar, Karpagam University, Coimbatore, Tamil Nadu.

Abstract--The work in this paper aims at designing

a multihop energy efficient, reliable and fault

tolerant routing protocol. It proposes to maintain an

asymmetric network of sensors so that the nodes get a

chance to configure their transmission ranges best,

and thus delivers data to the base station using as

little energy as possible. Our protocol design

concentrates on the load sharing feature by

maintaining multiple routes and selecting the best one

for relaying the data packets. It assigns different

transmission powers to different nodes based on the

network topology. The problem of bottleneck around

the base station is addressed by varying the

transmission ranges of the nodes periodically, which

changes the topology, to balance the responsibility

among the nodes across the network.

Index Terms— multihop energy efficient, reliable

and fault tolerant routing, multiple routes,

bottleneck.

I. INTRODUCTION

The work reported in this thesis aims at designing

of a multihop energy efficient, reliable and fault-tolerant

routing protocol. In a fully connected network, all nodes

can directly access the base station. However, wireless

being a broadcast medium, the congestion [1] in such a

network is very high. Typically, each node in a multihop

WSN would discover a path to the base station and route

its data through this path. This causes the nodes near the

base station to be used more frequently than the nodes

away from the base station. The reason is the former set

of nodes not only send their own sensed data, but are

also responsible for forwarding the packets from the far

off nodes in the network. This results in a bottleneck

around the base station. If the nodes around the base

station go dead, then the nodes away from base station

will be unable to send the data unless they increase their

transmission ranges. Figure Fig 1 shows an example of a

typical sensor network. The filled black node is the base

station. The lines depict the connectivity and the filled

gray nodes are the normal sensing nodes.

In this example node-2 and node-3 are one hop

nodes. Node-2 is responsible not only for sending its

own data but also for forwarding the data from nodes-4,

5, 6, 9 and 10. Similarly, node-3 is responsible for

sending its own data and as well as forwarding data of

nodes-7, 8, 11 and 12.

Thus the nodes situated at a distance of one hop from

base station are used more often than the other nodes. It

causes such nodes to dissipate energy at a substantially

higher rate than the rest of the nodes in the network [3].

Consequently, the network becomes dead very soon. The

residual energy in the nodes near the base station may be

sufficient to sense, but may not be sufficient

communicate the sensed data to the base station. This

observation led us to think how a routing protocol may

avoid the formation of transmission bottleneck around

the base station.

Fig-1. Example of a typical sensor network

The underlying idea is to ensure that the energy

dissipation at each node is more or less same over the

entire network. The approach we devised is to adjust

transmission range of individual nodes to provide

connectivity of base station without involving the nodes

near the base station as and when desired. It led to

dynamicity in the sensor network environment.



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We can view the dynamicity as insertion of new

nodes and deletion of nodes (node failure) at random

time. Our second observation is that WSNs experience

high packet losses. So, reliability is also important for

WSN [2]. Transmission reliability can be achieved

through an acknowledgment based protocol. It helps in

deciding the requirement of retransmissions if the packet

loss occurs and thus increases the reliability. An usual

trend in protocol design suggests that the location

parameters play crucial role for the routing purposes.

The determination of position parameters requires use of

embedded GPS receivers. But with embedded GPS

receivers will make the sensor nodes substantially

expensive. Additionally, also the nodes will consume

more power. Therefore, our aim is also to ensure come

up with routing protocols which avoids use of location

based information.

1.1. Problem statement and the Challenges Involved

The investigation in this paper is oriented towards

the design a multi hop routing protocol for time driven

WSN which achieves following objectives.

Avoid the formation of the congestion bottleneck

around the base station

Handle dynamic changes in topology caused by

transmission power adjustments.

Handle node failures on existing paths by a novel

route repair procedure that leverages ability to

adjust node transmission range.

Ensure reliability through use of

acknowledgements and limited retransmission of

lost packets.

Improve the network lifetime by considering

residual node energy during route discovery.

Analyze and compare the new protocol with the

existing ones.

The objectives listed at items 1 and 5 are achieved by

better utilization of the resources and treating the

network as a dynamically changing asymmetric network.

The topology change in the network is mainly

determined by adjustment of transmission range from

time to time. The resulting change topology modifies

path from every node to base station. The routing

protocol is, therefore, is a mix of both proactive and

reactive protocol [4]. The tasks of route discovery and

route maintenance become more challenging in an

asymmetric network, as Hello messages can not be used

for such purposes in asymmetric links. The latency of

route discovery also has to be minimized. Balancing

distribution of load for routing (forwarding packets)

among the nodes shall ensure the uniform and better

resource utilization. The concept of asymmetric network

shall allow the nodes to use appropriate transmission

ranges, which is more suitable for its longer lifetime

depending on its position in the network.

The fault tolerance in routing protocols for WSN is a

novel idea. It has been possible to tolerate node failure

simply by eliminating failed nodes through a route

maintenance step. It involves the adjustment of

transmission power at some nodes for establishing

connectivity with the base station when the routes are

found to be broken due to node failures. We

experimented with up to 5% node failures [5] [6] . The

objective concerning reliability in transmission is

achieved by acknowledgments for the data packets. The

protocol supports at most three retransmissions of the

data packets to handle packet loss. The routing metric is

chosen by optimizing both latency of routes and residual

energies at the nodes. The other desirable property of a

protocol which is addressed is load sharing. The load for

routing data packets is distributed over the multiple

alternate paths available at a node. It ensures overall

better utilization of energy resources and effectively

extends lifetime of the network.

Finally, we performed simulation over OMNet++

261] and compared our results with other notable time

driven WSN routing protocols such as LEACH [14] and

SPIN [13]. Our results show performance enhancement

over symmetric routing protocols and over both SPIN

and LEACH even without data aggregation

II. RELATED WORKS

This chapter deals with related work and the

underlying concepts which form the basis of energy

aware routing protocols for WSN Section 2.1 explains

how simple routing ideas could lead to unnecessary

wastage of precious energy resources. Section 2.2 deals

with some initial thinking done by researchers on the

ways to avoid broadcast storm which appear to be the

main reason behind excessive energy wastage in

routings ideas based on flooding and gossiping. Section

2.3 describes a number of routing protocols, namely,

LEACH [14], PEGASIS [15] TEEN [17] and APTEEN

[16] which try to eliminate redundant data broadcast and

conserve the crucial energy resource by aggregation in

some way or other. Later, section 2.4 which are relevant

in context to this paper. The subject of discussion in

section 2.5 is the quality and reliability of data delivered

by the sensors.

2.1 Flooding and Gossiping

The conventional mechanism for relaying data from

individual sensors to base station is Flooding or

Gossiping. The underlying idea of flooding is that each

sensor on receiving a data packet broadcasts the same to

its every neighbor. This packet is further re-broadcast

until it arrives at the destination or the maximum

number of hops for the packet is reached. Quite

obviously, flooding raises unmanageable broadcast

storms as depicted in Fig 2.1.



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Fig- 2.1: Broadcast storm

It may be appropriate for networks which experience

quick topology changes. WSN mainly consists of static

sensors nodes. So, topology remains more or less static

for a considerable period of time. Of course, it is possible

to control topology by adjusting transmission power of

sensor motes. But such power adjustments can only be

realized by program controls and hence, predictable. The

other serious problems with broadcast storm are

redundancies, contentions and collisions which result in

wasteful consumption of node energies. Since sensor

nodes have only limited energy reserves in the from of

small batteries, they can ill-afford such associated

problems arising out of broadcast storms [9]. Therefore,

flooding does not seem to be an appropriate approach of

design of routing protocols in WSNs. The deficiencies of

data reporting by flooding can be viewed under three

categories namely,

Implosion: it refers to nodes disseminating data

to all

of their neighbors regardless of whether the data

has already been received by these neighbors. It

result in wastage of energy across several nodes,

since the same piece of data arrives at every node

via multiple paths.

Overlap: it is not possible to have a precise

deployment whereby sensor could cover disjoint

spatial regions. So nodes often have overlapping

spatial coverage. Data dissemination by flooding,

therefore, results in data from overlapping regions

to be routed by different alternative sensors and

flooded over the network.

Resource ignorance: flooding does not require the

threshold. Consequently, a node may run out of

energy too soon to perform any meaningful data

sensing or reporting.

Gossiping is just a slightly enhanced version of

flooding wherein the recipient node sends the data

packet to a randomly selected neighbor [12]. That

neighbor in turn picks another random neighbor to

forward the packet to and so on. Another usual variation

of gossip protocol is that the recipients could

rebroadcasts or discard the data with probabilities p and

(1-p) respectively. By controlling the fraction of

executions where gossip die out relatively low and

keeping the gossip probability low it is possible to save

up to 35% message overhead compared to flooding [9].

But gossip based protocol exhibit bimodal behavior in

the sense that in almost all executions either most of the

nodes receive a message or hardly any of them do.

Furthermore, in many applications gossip delay may be

unacceptable.

2.2 SPIN and Directed Diffusion

The focus Sensor Protocols for Information via

Negotiation (SPIN) was to work around the problems of

simple flood based protocol mentioned in the previous

section. SPIN was successful in addressing all the

problems existing in the flood based protocols. It labeled

the data with the high level data descriptors, called

metadata. The metadata was used to negotiate between

the nodes, eliminating the redundant data from being

transmitted to the nodes [8] 11] . As the metadata was

supposed to be the compressed form of the original data

so, the network congestion could be avoided. So, the

SPIN mainly comprises of three phases.

STEP 1: Advertisement of the metadata

STEP 2: Request for the data

STEP 3: Actual data transmission.

There is also an energy efficient version of the SPIN in

which a node enters into this three way handshake only

if it has sufficient energy to complete it till the end.

SPIN not only achieved a considerable improvement

over flooding, but also instrumental to open up the

existing gaps in the research on routing protocols. It is

observed that the data actually traverses along multiple

paths but gets finally accepted from just one path, and

discarded from remaining others[13]. SPIN’s

implementation did not talk about the reliability which

may be one of the important issues in reliability

considering that the wireless networks are highly error-

prone. Fig 2.2 depicts the stepwise process.



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Fig-2.2. SPIN

Subsequently, a new protocol called Directed

Diffusion was proposed for event driven applications.

Directed diffusion concentrated on reducing the number

of multiple paths along which data traverses. It also

incorporates some novel features - data-centric

dissemination, reinforcement based adaptation to the

best path, in-network data aggregation, and caching. A

central controller called Sink injects its interest in the

network by normal flooding with a large update

interval. Sensors report data if they match with the

interest received from the sink node. A sensor sends to

the interested node through multiple paths. The

neighboring node establishes a gradient towards each

other based on the direction from which they have

received interest[7] [10]. This way the interested data

finds its path to the sink. Apart from being unsuitable

for continuous data delivery, it incurs extra overhead for

data matching and interest injection.

2.3 Aggregation Protocols

Considering that the sensors are resource constraint,

and the existing inherent redundancies which

characterizes data reporting in SPIN as well as directed

diffusion, a lot of scope for improvements were there.

LEACH is another protocol in line to throw some light

on the same issues and propose some more

improvements. The basic idea employed in LEACH is

cut down the overhead by reduce volume of data

reportage. LEACH[14] is an energy efficient,

aggregation protocol. It includes cluster formation and

local processing to reduce global communication by

collecting the packets of all the nodes in the cluster in

one place and aggregating the information contained.

The randomized rotation of the cluster-heads helps in

implementing the load sharing property. The LEACH

protocol involves the following steps:

STEP 1: Status collection of all nodes by the base

station.

STEP 2: Selection of the cluster heads by the base

station.

STEP 3: Choosing of the best cluster head by the node

STEP 4: Data dissemination to the cluster head

STEP 5: Aggregated data dissemination to the base

station by the cluster heads.

The problem with LEACH is that it considers all the

nodes to have accessibility to the base station when it

becomes the cluster head or when sending the status

message to the base station. According to the MICAz

specifications, the maximum outdoor transmission range

which is allowed for a node is 100m. The indoor

transmission range is even less, it is 30m at the

maximum. That means, to provide one hop connectivity

the maximum distance of a node from the base station

can be at most 100m. If the base station is placed at edge

of the network area then the maximum area which can

be allowed in LEACH. In LEACH each node decides its

cluster head based on which of the heads is closest to it.

It means that the location parameter plays an important

role here. The nodes need to know the position

coordinates of all the cluster heads chosen for that

round. LEACH needs GPS enabled node, which requires

considerable amount of energy apart from making the

sensor motes quite expensive.

The original LEACH proposal provisions for 5% of the

total nodes to be selected as the cluster head. With 100

nodes, the number of clusters formed will be 5. Given

that the maximum area which can be covered is 785m2.

Therefore, even after using so many nodes in such a

small area, the actual data transferred to the base station

is not much. If the volume of data to be transferred to the

control-center is considerable then either the number of

nodes must be increased or the percentage of the total

nodes selected as the cluster heads should be increased.

The energy dissipation at nodes is proportional to the

square of the distance from the destination, therefore,

the node which dies first is always the farthest nodes.

LEACH is not an acknowledgement based protocol. So,

the nodes receive no information of data being lost or

corrupted on the way to the destination. The protocol,

therefore, lacks reliability. The wireless networks are full

of noisy interferences and LEACH does allow any

redundancy in data, as the aggregation removes

redundancy, so non-reliable nature can be considered as

one of the major drawbacks.



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Although the LEACH does not talks directly about

asymmetric links, nor does introduce the concept, it is

implicit from the explanation that the nodes adjust their

transmission range every time they need to

communicate, based on their distance from the node

with which they want to communicate[19] [20]. In a

sense, the network can be considered to be asymmetric.

The asymmetric nature of the network here does help in

avoiding the wastage of energy and congestion, but as

the protocol is not implemented in a distributed way, the

asymmetric characteristic is under emphasized. Rather it

is considered a network with nodes having adjustable

transmission range. Environmental energy harvesting

has also been considered for improving the sustainable

lifetime of the resource constraint network. Numerous

harvesting modalities have been suggested including

solar, vibrational, biochemical, and light. A successful

demonstration of the solar energy. The SOLAR-aware

LEACH aims at extending the lifetime of the sensor

network by choosing solar-aware nodes as the preferable

cluster heads. While the harvesting energy provides the

ability to extract energy from the environment, it must

be efficiently integrated into an embedded system to

translate that harvested energy into increased application

performance and the system lifetime. This shows that

harvesting itself is very complex. The other drawback

being that the solar energy harvesting requires outdoor

system deployment, thus does not work for the indoor

networks.

Lindsay and Raghavan [19] proposed Power Efficient

Gathering in Sensor Information Systems (PEGASIS)

which achieved about 100-300% improvement over

LEACH over a range of percentages of nodes dying out

in different network sizes. In PEGASIS sensor nodes

form a chain to transmit and receive the data. Each node

transmits or receives data from a neighbor and only one

node from the chain is selected to send the data to the

base station. Each node on receiving the data aggregates

it to its own data and then transmits further. The

aggregated data is eventually sent to the base station.

The chain construction is done in a greedy way. Fig 2.3

illustrates that node-0 transmits data to node-1. Node-1

aggregates it to its own data and transmits it to the node-

2. Similarly, node-4 transmits its data to node-3. Node-3

aggregates it to its own data and transmits it to the node-

2. The node to finally aggregates all the received data

along with its own and relays it to the base station.

Fig-2.3: PEGASIS

Unlike LEACH, PEGASIS uses multihop routing and

only one node sends the data to the base station.

Although, PEGASIS shows 100--300% improvement

over LEACH for different network and topologies, there

are many issues which cannot be neglected when

analyzing a protocol. There is only one packet which is

reported to the base station every second, no matter how

large a network may be. The nodes are supposed to be

power adjustable do that if they are eventually selected to

the send the final packet to the base station, then many

must be able to do it in one hop. This again brings to us

the constraint of maximum power which a node can

possess [22]. Given that the maximum outdoor range is

100m, restricts the area which can be covered by

PEGASIS. As PEGASIS reduces the redundancy to zero

in the network, there is expected to be some scheme to

ensure reliability which is again absent.

Threshold sensitive Energy Efficient sensor Network

(TEEN) proposed by Manjeshwar and Agrawal is

actually the modified version of LEACH [14]. The

modification proposed was to convey two attributes to

the nodes from the cluster heads, namely, (i) Hard

Threshold and (ii) Soft Threshold. Hard threshold was

the absolute value of the sensed parameter beyond which

the value must be transmitted to the cluster head. Soft

threshold was the value of the sensed parameter beyond

which the node must activate its transmitter. As the data

was expected to be transmitted less frequently than being

sensed, so the protocol is much more energy efficient

then LEACH. But there are drawbacks which cannot be

neglected. If the threshold is not reached then data is not

communicated to the base station[23] [24]. There were

no messages to inform the base station that whether the

node has gone dead or the data is not crucial enough to

be reported. Thus, the reliability of data reportage

becomes an important drawback. Adaptive Periodic

Threshold sensitive Energy Efficient sensor Network

APTEEN was designed to remove the drawbacks of

TEEN. APTEEN adds an extra attribute to the packet

sent by the cluster heads to the cluster members.



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It not only includes the thresholds but also includes the

maximum interval between two packets. This

modification makes the protocol usable even by time

driven networks.

III. PROPOSED SYSTEMS

Wireless Sensor Networks (WSNs) like mobile

adhoc Networks (MANETs), are self-configuring

networks. But unlike MANETs, they are statically

deployed and each WSN has a central authority, known

as base station. Each sensor performs the sensing task

independent of others, but the routing of the sensed data

to the base station needs communication among the

nodes. Sensor nodes do not communicate except for

forwarding data to the base station or helping in

disseminating data from the base station. Therefore,

when determining the routes in a WSN, single

destination shortest paths is needed. Sensing requires

very little energy as compared to communication

Typically, the major physical layer property which is

assumed to be fixed in design of a routing protocol for

WSNs is the node transmission power. The network with

nodes having uniformly fixed transmission power are

referred to a symmetric networks. The traditional

protocol stack independently models the physical layer

and the higher layers. The abstraction of one layer is

added to the other layer to provide power of multi-

layering. Power control is very important in designing of

any protocol for wireless sensor networks as the nodes

are battery dependent. To control the energy

consumption at the nodes, the transmission range could

be varied. But, the variation should be done considering

the fact that the nodes have at least one path to the base

station and at the same time do not increase their

respective transmission ranges so as to give rise to a

densely connected graph. The configuration of the

physical layer properties at the startup time needs

hardware instructions. The transmission range is

adjusted thereby to get the best results at the network

layer.

When working with asymmetric networks the

physical layer properties come into picture very often, as

transmission range is required to be adjusted from time

to time. The current chapter of this thesis deals with a

proposal for a new routing protocol based on the above

principle of cross layer optimization. Extensive

simulations were carried out to compare the proposed

protocol with some existing protocols. The simulated

protocols include SPIN, LEACH and the two versions of

symmetric protocols. The symmetric protocol versions

are based on DSDV, so minimum hop count has been

used as routing metric.

3.1 Energy-aware Protocols

The research on energy-aware protocols for WSN has

so far focused on two major strategies to optimize energy

usage, viz., (i) reducing transmission of redundant data,

and (ii) confining communication to local sub-regions

(clusters) by partitioning areas of sensing environment.

Two well known protocols, namely SPIN and LEACH

which we chose to simulate are the representative cases

of the above two strategies. We also simulated two

versions of symmetric protocols. The characteristics of

symmetric protocol versions are as follows:

The basic protocol is a modification over

Destination Sequenced Distance Vector

(DSDV) protocol for adhoc networks. The

routing metric used is minimum hop count. The

routing in the first version does not have any

energy optimization criterion.

The second version attempts to make the first

version energy efficient by introducing residual

energy consideration.

The newly proposed asymmetric routing protocol has

been simulated with the purpose of comparing it with

the existing work. We looked at the following three

versions of the proposed protocol.

The first version is just a simple (no energy

consideration) routing protocol that works. for

asymmetric network. It uses minimum hop count

as the routing metric

The second version proposes to make the above

protocol energy efficient by introducing the

consideration of residual energy while relaying

the data.

The third version is adds an aggregation protocol

to combine residual energy consideration with

the idea of confining communication among

nodes locally.

3.2 Routing Protocols for Symmetric Networks

Since, WSNs are resource constraint, the most

important thing to be kept in view when designing a

routing protocol for WSN is that it should be (i) resource

aware, and (ii) should not be too complex to implement.

The symmetric routing protocol has been designed with

these two constraints in mind. The underlying idea is to

avoid flooding or injecting redundant data packets while

the data is being transmitted, a route discovery is

initiated or a route maintenance event occurs.

3.2.1 Multichip Minimum Hop count Protocol

Our first attempt is to find the shortest path between the

nodes and the base station and to be able to maintain it

in a distributed way. We have employed

acknowledgements for the data packets to ensure data

transmission reliable.



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Route Discovery

Normally, route discovery in symmetric networks is

performed in top-down fashion. The base station

initiates a route discovery process by sending a broadcast

message to all the neighbor nodes. Each node caches a

routing table which contains the preferred neighbor and

the hop count of the path. Fig 3.1 illustrates the fields of

routing table.

Fig-3.1.Routing Table

The receiving node updates its routing table and

rebroadcasts the request packet including its own details

downstream towards destination. The updates are

performed only if the hops reported by the route

information packets are less than the hop count of the

path cached. The route discovery process is a one time

task which is performed at the network startup.

Route Maintenance

Symmetric networks use periodic Hello packets to

maintain network topology. A Hello packet tells a node

about the status its neighbors. These packets contain

routing table information of the neighbors. When

relaying any data packet along the preferred neighbor,

the node checks whether it has received Hello message

from that neighbor or not. If no hello packet is received

from that neighbor for a long time then that neighbor is

considered to be dead or out

of service for the time being. If the frequency of these

packets is low then it takes long time to determine a

non-functioning route. Consequently, all the packets

routed through existing routes may either be dropped or

have to be retransmitted. Therefore, it necessitates

frequency of Hello packets sending to be substantial in

the case of time-driven networks.

Reliability

The wireless medium is not a reliable medium, as it

experiences interferences and noises from various

sources. The reliability has to achieve by designing a

robust protocol. Thus, our design is an

acknowledgement based protocol. The acknowledgement

is sent by base station on receiving a data packet. The

sender nodes caches the send packet till it receives an

acknowledgement. A data packet may be retransmitted

three times in the case of subsequent failures.

If failure occurs even after the three successive

retransmission, then the packet is discarded and the

cached neighbor is invalidated. The node is then left

with no valid path to relay the data packets. But as it

keeps on receiving the periodic Hello packets from its

neighbors, it may cache the sender of the next Hello

packet as the preferred neighbor. Later, it can update its

cache if any other Hello packet offers a better path in

terms of the hop count.

Evaluation of the Protocol

Although the above routing protocol perform better

than the traditional protocols like flooding gossiping,

SPIN, still there are certain problems. In the routing tree

the nodes near the base station are loaded with the

responsibility of relaying the data packets of the far-off

nodes well. Therefore, the nodes near the base station

exhaust their energy much before the far-off nodes. With

this, even if the far-off nodes have sufficient energy to

sense, they are unable to send data to the base station

because of the absence of a valid routing path. As the

links are required to be symmetric, all nodes need to

maintain same transmission power. Each node i select

the respective minimum level li at which they have at

least one path to the base station. The transmission

range is the maximum of the power level selected by

each node. So, a node has to maintain higher power

level even when it can possibly work well with lower

power. As already explained above, the Hello packets are

required to be more frequent than the data packets in

case of time-driven networks.

3.3 Routing Protocols for Asymmetric Networks

This work, as already stated, aims at proposing a

multihop energy efficient, reliable routing protocol for

wireless sensor networks. The idea is to retain the

positive characteristics of the existing protocols and

overcome the drawbacks. The protocol also targets to be

fault tolerant as well as scalable.

3.3.1 Energy Efficiency and Reliability

Our first target is to eliminate the bottleneck around

base station by sharing the responsibilities of data

transmission equitably among the near as well as far-off

nodes. It involves adjustment of per node transmission

power. The periodic variation in the transmission power

changes the network topology, and gives rise to

existence of asymmetric links in the network. It

maintains multiple optimal paths for communication, so

that an alternate path is available if one being used fails.



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Maintaining Discrete Levels

Our protocol maintains discrete levels of the

transmission range. The transmission ranges changes in

steps. Fig 3.3 depicts the changes in network topology

when the transmission range of the nodes changes in

step of 5. It may be observed that by adjusting node

transmission power, the number of nodes at one hop

distance from the base station changes.

Initially, as Fig 3.3 (a) shows, the transmission

range is 10m and the there are 2 nodes namely,

node-2 and node-3 at distance one hop to the

base station. So, the data transmission loads

from all the nodes get distributed among these

two nodes.

Fig 3.3 (b) depicts the change in topology when

the transmission range is 15m. There are four

nodes, viz., node-2, node-3, node-4 and node-5

at one hop distance to the base station. With

this new configuration, the load of data

transmission can now be distributed among four

nodes, implying lesser loads on node-2 and

node-3.

Fig 3.3 (c) gives the topology when the

transmission range is raised 20m. Now five

nodes, viz., node-2, node-3, node-4, node-5,

node-6 are at one hop distance from the base

station. As a result, the load of data

transmission can be distributed among five

nodes.

Fig-3.3. Topology variation: a) Transmission Range=10m

b) Transmission Range=15m c)

Transmission Range=20m

Thus, by regulating between the three transmissions

ranges periodically, we can avoid the bottleneck around

the base station. The lowest level transmission range of

different nodes may be different. It depends on the

position of a node in the network, so that the node

remains connected with the rest of the network, where

connectivity means existence of a route to the base

station. At a particular time instant two nodes can be at

different levels of transmission range.

The maximum level of transmission range is fixed based

on two conditions:

It should be large enough so that no node should

be left disconnected with this transmission range

when considering a symmetric network.

It should not be very large so as to make the

graph very densely connected and lead to wastage

of energy

resources.

The transmission range of the node increases in

levels. But there is no point in increasing the

transmission range of a node further once it has reached

the level when it is at one hop distance away from the

base station. This way the maximum transmission range

level attained by different node is different.

Transmission Range Period

The period for which a particular level should be

maintained is same for all nodes. This period is decided

based on number of nodes in the network, the

application and the area to be covered. The reason is:

sufficient time should be allowed for the newly formed

topology to converge. The time required to converge the

topology depends on the RTT (round trip time), since

the route discovery takes time proportional to RTT

(when done in bottom up fashion). The round trip time

is different for different nodes. It depends on the number

of hops (counted on the basis of initial transmission

range) between the node and the base station. As the

number of hops increases the round trip time increases.

The period of change of transmission range is required

to be large enough to allow the topology convergence.

Suppose the time taken to cover one hop distance is x

seconds. For N nodes the worst topology possible is

linear topology and so in worst case the hop count of a

node to reach the destination (base station) is N. In this

scenario the round trip time to discover the route is 2N x

seconds. Therefore, to provide enough time to a topology

to converge and use the discovered path, the

transmission range period should be greater than 2N x

seconds.

Route Discovery

The periodic changes in transmission ranges of

nodes create asymmetric networks. The process of route

discovery in such networks is different from that in

symmetric networks. In an asymmetric network a path

which may be valid from the base station to a node may

not be valid when reversed. The reason is some node-A

on the one way may be in range of other node-B, but

node-B might not be in the range of node-A. Fig 3.4

illustrates an example where there is a valid path 1-2-5-

9 from base station to node-9, but this path is not valid

in the reverse direction.



403

Fig-3.4. Asymmetric Network

In other words, node-9 can not reach 1 via the reverse

path 9-5-2-1. The data packets from node-9 can be

transmitted along the path 9-4-2-1. Such a path can be

discovered only by bottom-up approach and not in top-

down manner. The node which needs to discover the

route initiates a route request which is broadcast to all

the neighbor nodes. A node receiving the route request

packet checks for the staleness of the packet and on

finding it fresh rebroadcasts it further, till the request

reaches the base station. Assuming that the base station

is a powerful node (connected to stable power supply) so

it can reach all the nodes through one hop. The base

station sends back the reply which includes the preferred

neighbor of the requesting node. The base station avoids

sending the complete path by different nodes is different.

to the requesting node. It has three advantages:

The sending complete path would unnecessarily

increase the size of the reply packet.If the

number of nodes is N, assuming the worst case

topology (linear topology) the maximum number

of hop-counts to reach the destination (base

Station) can be as large as N. So, the size of the

reply packet may increase by a factor of N.

The requesting node caches only the preferred

neighbors id. If the complete path was to be

cached then memory (an important resource)

would be wasted for no fruitful reasons. _ If

complete path were cached then the nodes

caching the three paths to the base station has an

option of using one out of three alternate paths

available to a node. On the other hand, by

caching preferred neighbors, potentially more

alternate paths can be stored.

In Fig 3.5, the numbers in curly braces are the

cached ids of the preferred neighbors, and

arrows represent the connectivity. Consider for

example node-11, if the complete paths were

cached then the number of alternate paths

available is 3, i.e., {11-5-2-1, 11-6-3-1, 11-7-3-

1}. Whereas, if only the neighbors are cached

then the available number of alternates increase

to 5, namely, {11-5-2-1, 11-5-3-1, 11-6-2-1, 11-

6-3-1, 11-7-3-1}. Actually, if all the three

neighbors lead to three valid paths each, then the

potential number of number of alternate paths

could be as many as 3k, where k is the number of

hops from node to the base station.

To avoid the same request packet from being

rebroadcast by the same node, route request packet are

numbered. This sequence number is of the form <

node_id, request_no >. If node receives a request packet

with a repeated sequence number then that packet is

discarded. Thishelps in avoiding the loop formation in

the paths also removes unnecessary congestion in the

network.

Fig-3.5. Wireless Sensor Network

Acknowledgement Based Protocol

The protocol retains the reliable nature of symmetric

protocols by inheriting their acknowledgement

characteristic. The base station sends the

acknowledgements for the received data packets. Like

the previous case, there can be at most three

retransmissions in the case of delivery failures. If the

failure occurs for the fourth time, then the cached

neighbor is declared as invalid. After invalidating the

neighbor, if no cached neighbor is available, then

reactive route discovery takes place.

Route Maintenance

In asymmetric networks hello packets can serve no

purpose. Suppose node-A and node-B share an

asymmetric link. Even it a node A has direct access to

another node B, B may not have direct access A.



404

A could cache B as its neighbor for routing the data

packets to the destination. Since the hello packets from

B can not reach A, the use of these packets does not

work for maintaining routes in asymmetric networks.

Consequently, discovered routes in asymmetric network

are maintained in reactive manner. The initial route

discovery is done in a proactive way at the start of each

transmission period. Our design combines the

advantages of both proactive and reactive protocols. A

proactive protocol has low latency but discovers and

rediscovers routes which are not required, whereas are

active protocol discovers only the required routes but has

higher latency. In the proposed approach, the proactive

discovery of the routes is done when the node changes

its transmission range (change in transmission range is

periodic). The maintenance of routes is done in reactive

way. In case the acknowledgement is not received for

any data packet even after three retransmissions, the

path invalidated and a reactive route discovery takes

place.

3.3.2 Energy-Aware Routing

The second version of our proposed protocol is

designed to uncover the importance of residual node

energy in data transmission. It provides an integrated

approach to cache the residual energy of the preferred

neighbors and choose the best alternate available for

relaying the data packets.

Residual Energy Consideration

In the protocol for symmetric networks, the energy

updates were provided by the Hello packets. However, in

the light of the discussions in section 3.3.1, Hello

packets cannot help. Therefore, each node sends a

periodic energy update to the neighbors informing the

maximum level of the transmission power with which it

can operate. If the sender of the Energy Update packet is

cached as the preferred neighbor at the receiver, the

recipient also stores the updated residual energy value.

Since, energy update packets have no other purpose like

route maintenance, they can be sent less frequent than

route update packets (Hello packets) in symmetric

networks.

3.3.3 Role of Aggregation Protocol

We also integrated an aggregation protocol for data

transmission in the proposed energy aware routing

protocol the asymmetric network. There are many

applications where the precise location of data is not

important. In other words, the spatiality of data can be

extended to include data from any point within a sub-

region. So, it we may aggregate data from the cluster

members by either finding the mean, median, or mode,

then transmit a single value to base station. It helps to

eliminate spatial redundancy in the sensor data. An

example application can be temperature monitoring in

an area.

Cluster Formation

Typically, the cluster formation all the clustering

protocols is performed by the base station .ut our design

this unwanted overhead on the base station has been

eliminated by the distributed formation of the clusters.

Fig 3.6 shows

.

Figure 3.6: Aggregation in Asymmetric Network

explains the clustering process. The nodes sharing the

same preferred neighbor for a particular round forms a

cluster. For example, as node-2, 3, and 4 all have node-1

as their preferred neighbor, so these nodes belong to the

same cluster. Similarly, node-5, and 6 cache node-2 as

their preferred neighbor implying that {5, 6} form a

cluster. In all seven cluster can be identified in Fig 3.6.

These are: {(2,3,4), (5,6), (7,8), (9,10), (11,12), (13,14)}

3.4 Evaluation of the Proposed Protocol

Before carrying out empirical evaluation of the

proposed protocol through simulation, it is instructive to

identify the basic parameters on which an evaluation

should be based, and to qualitatively argue out the

reasons behind expecting improvements compared to

existing routing protocols for WSNs. In this section we

discuss about these parameters.

3.4.1 Improved Lifetime

The proposed protocol eliminates bottleneck around

the base station by periodic change of topology through

per node power adjustment. The protocol is resource-

aware as the preferred path is selected on the basis of the

maximum residual energy.



405

Therefore, the proposed protocol when compared

with the existing protocols should results in better

network lifetime.

3.4.2 Resource-awareness

The design is resource-aware as is chooses the path

with maximum residual energy from among the existing

alternatives, for relaying the data packets to the base

station.

3.4.3 Reduced Message Complexity and Zero

Redundancy

There exists no redundancy in transmission of the

data packets. The redundancy in the route request

packets has been avoided by using the request ids in the

respective packets. Every node caches at most three

neighbors to be used as the preferred next hops for

relaying the data. Once three neighbors have been

discovered, further discovery is considered redundant.

The base station uses a REQ_CAN packet, which

contains the id of the requesting node and the sequence

number of the request. It is broadcast by the base station

once three neighbors for any node are discovered. Any

node on receiving this packet discards the route request

quoted by the REQ_CAN packet. Thus, this packet is

used as a death certificate for the route request packets

from a particular node and a specific sequence number.

3.4.4 Reliability

As the redundancy is reduced to the minimum level,

the overhead due to reliability is required to be

considered. There are acknowledgements for the data

packets. The protocol design supports at max three

retransmissions of a data packet. There is trade-off

concerning reliability versus redundancy. But reliability

in a way helps to eliminate requirement for redundancy.

3.4.5 Scalability

The protocol puts no constraint of the deployment

area. New nodes can be injected to the network. A new

node performs a reactive route discovery for a path to the

base station. It can be used as a forwarding node only

after the next proactive discovery takes place, or if there

is any reactive discovery before the next proactive

schedule.

3.4.6 Fault Tolerance

The protocol is dynamic enough to handle the node

failures. If a node fails, the packets relayed along that

path will result in no acknowledgements, so the paths

will be invalidated after three retransmissions.

If on invalidating the path, a node is left with no valid

path, it reactively starts

a new route discovery.

3.4.7 Load Balancing

Each node maintains three alternate preferred

neighbors to be used for relaying the data to the base

station. As the best is chosen based on the maximum

residual energy, the load is balanced among the three

neighbors.

3.4.8 Requirements for Specialized Support Parameters

Some routing protocols like LAR [15] or GAF [29]

make use of position vectors of the nodes to eliminate

flooding during route discovery. However, our proposed

protocol does not require any such additional support.

The protocol works independent of the location of the

individual nodes. Therefore, suited both for indoor and

outdoor networks. The routing algorithm is simple to

implement.

IV. SIMULATION RESULTS

In this chapter we present the results of

experiments carried out for evaluating the performance

of the proposed energy efficient routing protocol. For a

evaluation to be meaningful, the performance of the

proposed protocol should be compared with the

performances of certain well known existing energy

aware protocols. We base our evaluation primarily by

comparing with the performance of two other protocols,

namely, SPIN [11] and LEACH [12]. The choice of

these two protocols for performance comparison is

guided by two important reasons. SPIN’s approach is

based on eliminating data redundancies due to impolsion

and overlaps exhibited by plain flooding. On the other

hand, LEACH’s approach is to form random clusters in

each round so that the load of data transmission borne by

the cluster heads can be spread uniformly over all nodes.

So, LEACH cuts back overheads due communication by

localizing most of the communication through data

aggregation.

Since, the proposed protocol leverages cross layer

optimization for energy efficiency in WSN routing, it

should independently show performance enhancement

over symmetric routing protocols and over both SPIN

and LEACH even without data aggregation. The results

are discussed through plots accompanied by explanation

as needed.The simulation environment consists of 80

nodes uniformly randomly distributed over a space of of

(125X190)m2 Certain experiments have also been done

to see the effect of change in the network density over

the lifetime.



406

The node attributes chosen to strongly resemble

MICAz motes. A MICAz mote is a 2.4 GHz, IEEE

802.15.4 complaint chip. The mote module used for

enabling low power wireless interface. Since the indoor

range of for the sensor networks is 20m � 30m, the

transmission range variations are applied within this

range. As specified in the IEEE 802.15.4, we have used

the standard data packet size of 128b y tes. The

simulation assumes the base station to be fixed at the

origin and is a powerful node.

4.1 Node Placement

The plot in Fig. 4.1 shows the distribution of the

nodes. The base station or the control center is placed at

the origin, i.e., (0,0). The position of the other nodes are

randomly generated by the simulating software.

Fig- 4.1. Node Placement

The distribution followed is the random uniform

distribution. A black dot displays the position of a node,

the id of the node is written alongside the dot. The base

station id is 1, and the 80 sensor nodes are allocated ids

from 2 to 81.

4.2 Network Lifetime

As, already mentioned, one of the major objective of

this work has been to improve the lifetime of the sensor

networks. So we compare the lifetime in the proposed

methodology with the existing protocols. Typically, there

are three different measures for the lifetime of a WSN,

namely,

1. The time till the first node exhaust its energy,

2. The time till the last node exhaust its energy, and

3. The time till half the nodes in the network exhaust

their energy.

In this work, The first parameter has been used for the

purpose of comparison of different protocols.

Fig-4.2. Lifetime

The plot in Fig. 4.2 shows the improvement in the

lifetime obtained with the proposed methodology over

the existing symmetric protocol semantics. The five

protocols compared in this section are

SPIN: The transmission range of the nodes is

taken to be 29m, as this is the minimum range

when all nodes get at least one path to the base

station.

Symmetric Protocol: The transmission range used

is same as above.

Symmetric protocol with Residual Energy

Consideration: The transmission ranged used is

same as above.

Asymmetric Network: In this all nodes change their

transmission range between a fixed range in steps.

Parameter values:

1. Transmission Range: 20m�32m

2. Transmission Period: 12Nsec

3. Step Size: 3m

4.Asymmetric protocol with Residual Energy

Consideration: All the parameters are kept unchanged as

above. The Energy update packets are broadcast to the

neighbors every 5 secs.

4.3 Effect of Node Failure

The plots in this subsection are used to observe the

effect of node failure on the lifetime of the network when

the nodes near the base station fail.



407

The network configuration used for the purpose of

evaluation is as follows:

1. The period of the transmission range: 12Nsec.

2. The range between which transmission power is

varied: 20m to 32m.

3. The steps in which transmission range is varied:

6m.

4. The variation in percentage of node failures: 1%-

5%.

Fig-4.3. Effect of node failure on Lifetime

There is a trade-off between the following:

1. The total energy drained out of the network because of

the packets generated by centrally located nodes,

2. The total energy saved by the far-off nodes when they

use those centrally located for routing data packets.

The plot in Fig. 4.3 shows the effect on the lifetime of

the network when nodes far-off from the base station

fail. If the far-off nodes die then the lifetime shows an

improvement of about 7% with 5% nodes going dead. It

happens because the load due to the route discovery and

the data packet of the far-off nodes reduces. The nodes

near the base station are now less loaded and last longer.

4.4 Effect of Aggregation

The aggregation version of the proposed protocol has

been compared with the well known aggregation

protocol LEACH [12]. The lifetime obtained with

proposed approach was 150400sec which shows an

improvement of more than 400% is observed over

LEACH (27099sec). As already stated in chapter 2,

LEACH is not suited for such large area.

But still if we remove the constraint of the

transmission range and assume to use nodes with very

high transmission ranges, that is maximum of

approximately 250m, the proposed protocol outperforms

LEACH.

4.4.1 Clusters in LEACH

Although as mentioned in the chapter 2, LEACH can

work in this configuration with the assumption that the

nodes are able to increase their transmission range to

around 250m, the number of clusters to be formed are

taken to be 20% of the number of nodes. If the number is

higher then the performance goes down further. Since,

the total number of nodes is 80, the highest number of

clusters formed at any particular instant of the

simulation was 16. The total area covered by each

cluster is approximately 1500m2, which is large enough.

Fig-4.4. a) Clusters in LEACH

4.4.2 Effects of Aggregation in Proposed Protocol

The graph in Fig. 4.4. b) shows that by introducing

aggregation in the proposed asymmetric protocol,

around 40 clusters are formed at any particular instant of

the simulation. Therefore, the number of packets

delivered is much more than in the case LEACH as

depicted in Fig. 4.4. a). The total area covered by each

cluster in case of the asymmetric network is

approximately 600m2 which leads to better localization

of communication We addressed the following issues

through our experiments.



408

Energy efficiency: The lifetime of the network

increased by about 155% in comparison to the

symmetric network.

Scalability: The protocol is dynamic enough to handle

the failures and new insertions.

Low latency: As the protocol is a mixture of both

proactive and reactive protocols, the total delay factor is

3RT T + k, where k is a parameter introduced due to

congestion Reliability: It is an acknowledgment based

protocol. If acknowledgment is not received for a packet

till acknowledgment timeout, retransmissions take place.

Easy to implement: The implementation details

presented, clearly shows that the protocol is easy to

implement.

Fig-4.4.b) Clusters in Asymmetric Network with

Residual Energy Consideration

V. CONCLUSION

The work in this thesis is focused towards designing,

implementation and evaluation of energy efficient

routing protocols for wireless sensor networks. The

elimination of bottleneck around the base station is a

matter of major concern. The effort was directed towards

uniform distribution of data transmission and

dissemination load among the nodes across the network.

We realized that only way to achieve this is to develop a

methodology for distributed topology control. We

studied the specification of MICAz motes and came to

conclusion that by per-node transmission power

adjustment, it is possible to control topology and thus

eliminate the bottleneck around the base station.

It resulted in increase in the lifetime of the network.

Through a series of simulation experiments using

different network configurations, we observed that the

approach is justified and result in substantial

performance enhancements over existing energy aware

protocols. The proposed protocol when compared to the

symmetric multihop protocol was found to attain 155%

improvement in the lifetime. The aggregation version of

the proposed protocol showed an improvement of 400%

over the existing aggregation protocol LEACH.

REFERENCES

[1]. C. Schurgers and M. B. Srivastava, “Energy efficient

outing in wireless sensor networks,” in Proc. IEEE

Military Communications Conf. (MILCOM), 2001, pp.

357–361.

[2] D. Ganesan, R. Govindan, S. Shenker, and D. Estrin,

“Highly-resilient, energy-efficient multipath routing in

wireless sensor networks,” SIGMOBILE Mobile Comput.

Commun. Rev., vol. 5, no. 4, pp. 11–25, 2001.

[3] R. Shah and J. Rabaey, “Energy aware routing for low

energy ad hoc sensor networks,” in Proc. IEEE Wireless

Communications and Networking Conf. (WCNC), 2002,

pp. 350–355.

[4] J.-H. Chang and L. Tassiulas, “Maximum lifetime routing

in wireless sensor networks,” IEEE/ACMTrans. Netw., vol.

12, no. 4, pp. 609–619, Aug. 2004.

[5] G. Park, S. Yi, J. Heo, W. C. Choi, G. Jeon, Y. Cho, and C.

Shim, “Energy aware routing with dynamic probability

scaling,” in Lecture Notes in Computer Science. New

York: Springer, 2005, vol. 3642, pp. 662–670.

[6] C. Lu, B. Blum, T. Abdelzaher, J. Stankovic, and T. He,

“RAP: A real-time communication architecture for large-

scale wireless sensor networks,” in Proc. IEEE Real-Time

and Embedded Technology and Applications Symp.

(RTAS), 2002, pp. 55–66.

[7]. Wendi Heinzelman, Anantha Chandrakasan, and Hari

Balakrishnan. Energy-efficient communication protocols

for wireless microsensor networks. In Proceedings of the

33rd Annual Hawaii International Conference on System

Sciences, 2000, pages 10 pp. vol.2–, Jan 4-7, 2000.

[8] B. Hull, K. Jamieson, and H. Routing protocols overview

and design issues for selforganized networks. In

International Conference on Communication Technology

(WCCICCT), volume 2, pages 1298–1303, 2000.

[9] Chalermek Intanagonwiwat, Ramesh Govindan, and

Deborah Estrin. Directed diffusion: a scalable and robust

communication paradigm for sensor networks. In

MobiCom ’00: Proceedings of the 6th annual international

conference on Mobile computing and networking, pages

56–67, New York, NY, USA, 2000. ACM Press.

[10] Young-Bae Ko and Nitin H. Vaidya. Location-aided

routing (LAR) in mobile ad hoc networks. volume 6, pages

307–321, 2000.

[11] Philip Levis, Nelson Lee, Matt Welsh, and David Culler.

Tossim: accurate and scalable simulation of entire tinyos

applications. In SenSys ’03: Proceedings of the 1st

international conference on Embedded networked sensor



409

systems, pages 126–137, New York, NY, USA, 2003.

ACM.

[12] F. L. Lewis. Wireless sensor networks. In D. J. Cook and

S. K. Das, editors, Smart Environments: Technologies,

Protocols and Applications, pages 12–13. John Wiley,

New York, USA, 2004.

[13] X. Lin, N. B. Shroff, and R. Srikant. A tutorial on cross-

layer optimization in wireless networks. IEEE Journal

onSelected Areas in Communications, 24(8):1452–1463,

2006.

[14] Stephanie Lindsey and Cauligi S. Raghavendra. Pegasis:

Power-efficient gathering in sensor information systems,

2002.

[15] Arati Manjeshwar and Dharma P. Agrawal. Teen: A

routing protocol for enhanced efficiency in wireless sensor

networks. 15th International Parallel and Distributed

Processing Symposium (IPDPS’01), 03, 2001.

[16] Wendi Heinzelman, Anantha Chandrakasan, and Hari

Balakrishnan. Energy-efficient communication protocols

for wireless microsensor networks. In Proceedings of the

33rd Annual Hawaii International Conference on System

Sciences, 2000, pages 10 pp. vol.2–, Jan 4-7, 2000.

[17] Arati Manjeshwar and Dharma P. Agrawal. Apteen: A

hybrid protocol for efficient routing and comprehensive

information retrieval in wireless sensor networks. In

IPDPS ’02: Proceedings of the 16th International Parallel

and Distributed Processing Symposium, page 48, 2002.

[18] J. Neander, E. Hansen, M. Nolin, and M. Björkman.

Asymmetric multihop communication in large sensor

networks. In Wireless Pervasive Computing, 2006 1st

International Symposium on, pages 7 pp.–, 16-18 Jan.

2006.

[19] J. Neha, D. K. Madathil, and D. P. Agrawal. Exploiting

multi-path routing to achieve service differentiation in

sensor networks. In 11th IEEE International Conference

on Networks (ICON), pages 681–686, October, 2003.

[20] Kumar Padmanabh and Rajarshi Roy. Bottleneck around

base station in wireless sensor network and its solution. In

Mobile and Ubiquitous Systems - Workshops, 2006. 3rd

Annual International Conference on, pages 1–5, 17-21

July 2006.

[21] Charles Perkins and Pravin Bhagwat. Highly dynamic

destination-sequenced distancevector routing (DSDV) for

mobile computers. In ACM SIGCOMM’94 Conference on

Communications Architectures, Protocols and

Applications, pages 234–244, 1994.

[22] Sharmila Ravula, Ji Eun Kim, Brad Petrus, and Christoph

Stoermer. Quality attributes in wireless sensor networks.

Third IEEE Workshop on Software Technologies for

Future Embedded and Ubiquitous Systems (SEUS’05),

00:30–32, 2005.

[23] Rahul C. Shah and Jan Rabaey. Energy aware routing for

low energy ad hoc sensor networks. In Wireless

Communications and Networking Conference, 2002.

WCNC2002. 2002 IEEE, volume 1, pages 350–355, 17-21

Mar 2002.

[25] Ya Xu, John Heidemann, and Deborah Estrin. Geography-

informed energy conservation for ad hoc routing. In

MobiCom ’01: Proceedings of the 7th annual international

conference on Mobile computing and networking, pages

70–84, New York, NY, USA, 2001.

[26]. ACM. Documentation and tutorials for omnet++.

http://www.omnetpp.org/.

[27]Micaz 2.4 ghz data sheet.

http://www.davidson.com.au/products/wireless/

crossbow/mica-2-4.asp. [26]The network simulator ns-2.

http://www.isi.edu/nsnam/ns.

AUTHORS PROFILE

K.Vinoth Kumar received the B.E. degree in electronics and communication engineering from the Kurinji College of engineering and technology, Manapparai, Anna University, Chennai, India, in 2009. He received the M.E. degree in Applied electronics from the J.J College of engineering and technology, Trichirappalli, India, in

2011. Currently doing Ph.D. in communication and Networking in Karpagam University Coimbatore. His research interest includes wireless communication, Mobile Ad hoc networks, Sensor Networks, Communication networks.

S.Karthikeyan received the M.Sc

degree in Industrial electronics from

the M.I.E.T, college of arts and

science, trichirappalli India, in

2011.Currently doing M.E. in VLSI

design in Karpagam University

Coimbatore, India. His research

interest includes wireless

communication (WiFi,WiMax),

Mobile Ad hoc networks and low power VLSI

Paste

Photo

here

http://www.davidson.com.au/products/wireless/

http://www.isi.edu/nsnam/ns

multihop energy efficient reliable and fault tolerant routing

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